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Study: Danger of Driverless Vehicles Grows With Time

A driver’s ability to react to hazards undetectable to autonomous vehicles fell by as much as 21% after 40 minutes in simulator testing conducted by researchers from Rice University and Texas Tech.

Photo courtesy Rice University

HOUSTON — New research from Rice University and Texas Tech University has found that drivers often fail to spot hazards missed by automated vehicles, and it only gets worse the longer drivers ride in them. The study, “Driver Vigilance in Automated Vehicles: Effects of Demands on Hazard Detection Performance,” was co-authored by David Newton, a graduate student at Texas Tech, and will appear in an upcoming edition of Human Factors.

The researchers examined the behavior of 60 licensed drivers operating an automated car in a simulator. Participants were told they would not need to steer, brake, or accelerate. They were instructed to monitor the roadway for vehicles that were stopped dangerously at intersections and intruding into the driver’s lane, which constituted a hazard that automated vehicles could not detect. Participants also had to distinguish between vehicles that were safely stopped and dangerously stopped at intersections.

By the end of the 40-minute simulation, the drivers’ accuracy dropped by 7% to 21%. The highest score was just less than 88%, suggesting that all drivers missed at least some hazards.

Pat DeLucia, a professor of psychological sciences at Rice and the study’s co-author, said one possible explanation is that people get used to cars doing the driving and become complacent. Coupled with previous research that indicated people are “terrible” at monitoring for occasional hazards, the new study “suggests that this phenomenon of difficulty monitoring effectively over time extends to monitoring an automated car,” DeLucia said.

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